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        Download the raw data used to create the plots in this report below:

        Note that additional data was saved in multiqc_data when this report was generated.


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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.6

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/ewels/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2021-06-26, 09:26 based on data in: /home/veit/WOMBAT-P/OpenMS-ProteomicsLFQ/Nextflow/lowfragtol/results/proteomics_lfq


        ProteomicsLFQ

        proteomicslfq is an module to show the pipeline performance.

        HeatMap

        This plot shows the pipeline performance overview

        This plot shows the pipeline performance overview. Some metrics are calculated.

        • Heatmap score[Contaminants]: as fraction of summed intensity with 0 = sample full of contaminants; 1 = no contaminants
        • Heatmap score[Pep Intensity (>23.0)]: Linear scale of the median intensity reaching the threshold, i.e. reaching 221 of 223 gives score 0.25.
        • Heatmap score[Charge]: Deviation of the charge 2 proportion from a representative Raw file.
        • Heatmap score [MC]: the fraction (0% - 100%) of fully cleaved peptides per Raw file
        • Heatmap score [MC Var]: each Raw file is scored for its deviation from the ‘average’ digestion state of the current study.
        • Heatmap score [ID rate over RT]: Scored using ‘Uniform’ scoring function.
        • Heatmap score [MS2 Oversampling]: The percentage of non-oversampled 3D-peaks.
        • Heatmap score [Pep Missing]: Linear scale of the fraction of missing peptides.
        loading..

        Experimental Design

        This plot shows the Proteomics Experimental Design

        This plot shows the Proteomics Experimental Design. You can see details about it in https://abibuilder.informatik.uni-tuebingen.de/archive/openms/Documentation/release/latest/html/classOpenMS_1_1ExperimentalDesign.html

        Showing 27/27 rows and 6/6 columns.
        Spectra FileFraction_GroupFractionLabelSampleMSstats_ConditionMSstats_BioReplicate
        UPS1_12500amol_R1.raw
        1
        1
        1
        1
        CT=mixture;QY=12500 amol;CN=UPS1;CV=Standards Research Group
        1
        UPS1_12500amol_R2.raw
        2
        1
        1
        1
        CT=mixture;QY=12500 amol;CN=UPS1;CV=Standards Research Group
        1
        UPS1_12500amol_R3.raw
        3
        1
        1
        1
        CT=mixture;QY=12500 amol;CN=UPS1;CV=Standards Research Group
        1
        UPS1_125amol_R1.raw
        4
        1
        1
        2
        CT=mixture;QY=125 amol;CN=UPS1;CV=Standards Research Group
        2
        UPS1_125amol_R2.raw
        5
        1
        1
        2
        CT=mixture;QY=125 amol;CN=UPS1;CV=Standards Research Group
        2
        UPS1_125amol_R3.raw
        6
        1
        1
        2
        CT=mixture;QY=125 amol;CN=UPS1;CV=Standards Research Group
        2
        UPS1_25000amol_R1.raw
        7
        1
        1
        3
        CT=mixture;QY=25000 amol;CN=UPS1;CV=Standards Research Group
        3
        UPS1_25000amol_R2.raw
        8
        1
        1
        3
        CT=mixture;QY=25000 amol;CN=UPS1;CV=Standards Research Group
        3
        UPS1_25000amol_R3.raw
        9
        1
        1
        3
        CT=mixture;QY=25000 amol;CN=UPS1;CV=Standards Research Group
        3
        UPS1_2500amol_R1.raw
        10
        1
        1
        4
        CT=mixture;QY=2500 amol;CN=UPS1;CV=Standards Research Group
        4
        UPS1_2500amol_R2.raw
        11
        1
        1
        4
        CT=mixture;QY=2500 amol;CN=UPS1;CV=Standards Research Group
        4
        UPS1_2500amol_R3.raw
        12
        1
        1
        4
        CT=mixture;QY=2500 amol;CN=UPS1;CV=Standards Research Group
        4
        UPS1_250amol_R1.raw
        13
        1
        1
        5
        CT=mixture;QY=250 amol;CN=UPS1;CV=Standards Research Group
        5
        UPS1_250amol_R2.raw
        14
        1
        1
        5
        CT=mixture;QY=250 amol;CN=UPS1;CV=Standards Research Group
        5
        UPS1_250amol_R3.raw
        15
        1
        1
        5
        CT=mixture;QY=250 amol;CN=UPS1;CV=Standards Research Group
        5
        UPS1_50000amol_R1.raw
        16
        1
        1
        6
        CT=mixture;QY=50000 amol;CN=UPS1;CV=Standards Research Group
        6
        UPS1_50000amol_R2.raw
        17
        1
        1
        6
        CT=mixture;QY=50000 amol;CN=UPS1;CV=Standards Research Group
        6
        UPS1_50000amol_R3.raw
        18
        1
        1
        6
        CT=mixture;QY=50000 amol;CN=UPS1;CV=Standards Research Group
        6
        UPS1_5000amol_R1.raw
        19
        1
        1
        7
        CT=mixture;QY=5000 amol;CN=UPS1;CV=Standards Research Group
        7
        UPS1_5000amol_R2.raw
        20
        1
        1
        7
        CT=mixture;QY=5000 amol;CN=UPS1;CV=Standards Research Group
        7
        UPS1_5000amol_R3.raw
        21
        1
        1
        7
        CT=mixture;QY=5000 amol;CN=UPS1;CV=Standards Research Group
        7
        UPS1_500amol_R1.raw
        22
        1
        1
        8
        CT=mixture;QY=500 amol;CN=UPS1;CV=Standards Research Group
        8
        UPS1_500amol_R2.raw
        23
        1
        1
        8
        CT=mixture;QY=500 amol;CN=UPS1;CV=Standards Research Group
        8
        UPS1_500amol_R3.raw
        24
        1
        1
        8
        CT=mixture;QY=500 amol;CN=UPS1;CV=Standards Research Group
        8
        UPS1_50amol_R1.raw
        25
        1
        1
        9
        CT=mixture;QY=50 amol;CN=UPS1;CV=Standards Research Group
        9
        UPS1_50amol_R2.raw
        26
        1
        1
        9
        CT=mixture;QY=50 amol;CN=UPS1;CV=Standards Research Group
        9
        UPS1_50amol_R3.raw
        27
        1
        1
        9
        CT=mixture;QY=50 amol;CN=UPS1;CV=Standards Research Group
        9

        Summary Table

        This plot shows the ProteomicsLFQ pipeline summary statistics

        This plot shows the ProteomicsLFQ pipeline summary statistics

        Showing 1/1 rows and 2/2 columns.
        Total MS/MS SpectralTotal MS/MS Spectral IdentifiedIdentified MS/MS Spectral Coverage
        1035348
        383582
        37.05%

        Pipeline Result Statistics

        This plot shows the ProteomicsLFQ pipeline final result

        This plot shows the ProteomicsLFQ pipeline final result. Including Sample Name、Possible Study Variables、identified the number of peptide in the pipeline、 and identified the number of modified peptide in the pipeline, eg. All data in this table are obtained from the out_msstats file. You can also remove the decoy with the remove_decoy parameter.

        Showing 27/27 rows and 5/5 columns.
        Spectra FileSample Nameconditionfractionmodified_peptide_numprotein_num
        UPS1_12500amol_R1.raw
        1
        1
        0
        0
        UPS1_12500amol_R2.raw
        1
        1
        0
        0
        UPS1_12500amol_R3.raw
        1
        1
        0
        0
        UPS1_125amol_R1.raw
        2
        1
        0
        0
        UPS1_125amol_R2.raw
        2
        1
        0
        0
        UPS1_125amol_R3.raw
        2
        1
        0
        0
        UPS1_25000amol_R1.raw
        3
        1
        0
        0
        UPS1_25000amol_R2.raw
        3
        1
        0
        0
        UPS1_25000amol_R3.raw
        3
        1
        0
        0
        UPS1_2500amol_R1.raw
        4
        1
        0
        0
        UPS1_2500amol_R2.raw
        4
        1
        0
        0
        UPS1_2500amol_R3.raw
        4
        1
        0
        0
        UPS1_250amol_R1.raw
        5
        1
        0
        0
        UPS1_250amol_R2.raw
        5
        1
        0
        0
        UPS1_250amol_R3.raw
        5
        1
        0
        0
        UPS1_50000amol_R1.raw
        6
        1
        0
        0
        UPS1_50000amol_R2.raw
        6
        1
        0
        0
        UPS1_50000amol_R3.raw
        6
        1
        0
        0
        UPS1_5000amol_R1.raw
        7
        1
        0
        0
        UPS1_5000amol_R2.raw
        7
        1
        0
        0
        UPS1_5000amol_R3.raw
        7
        1
        0
        0
        UPS1_500amol_R1.raw
        8
        1
        0
        0
        UPS1_500amol_R2.raw
        8
        1
        0
        0
        UPS1_500amol_R3.raw
        8
        1
        0
        0
        UPS1_50amol_R1.raw
        9
        1
        0
        0
        UPS1_50amol_R2.raw
        9
        1
        0
        0
        UPS1_50amol_R3.raw
        9
        1
        0
        0

        Number of Peptides Per Proteins

        This plot shows the number of peptides per proteins in ProteomicsLFQ pipeline final result

        This statistic is extracted from the out_msstats file. Proteins supported by more peptide identifications can constitute more confident results.

        loading..

        Quantification Result

        This plot shows the quantification information of peptidesin ProteomicsLFQ pipeline final result

        The quantification information of peptides is obtained from the pep table in the mzTab file. The table shows the quantitative level of peptides in different study variables.

        Showing 47/47 rows and 1/1 columns.
        IDsequence
        1
        YPDIFPVMK
        2
        KSNHNSHSSK
        3
        PWNPPQK
        4
        KHTQHK
        5
        HHNEGTVSK
        6
        HEDVHR
        7
        KAEKPETK
        8
        QAQEILTK
        9
        IKHNKPK
        10
        YDSTHGR
        11
        ADELQK
        12
        HALHGTAK
        13
        QITVNDLPVGR
        14
        VLHHEK
        16
        QQNFVR
        17
        GHDSADHASQNSGGKPR
        18
        RGNVCGDAK
        19
        SKNHTAHNQTR
        20
        DKEACVHK
        21
        LELIELLEK
        22
        TVDGPSHK
        23
        KSCHTAVDR
        24
        HLKSEDEMK
        25
        HAHGDQYK
        26
        ERLGPLILQR
        27
        HIDAGAKK
        28
        SEYVHHK
        30
        KKDDVVK
        31
        KRPVPK
        33
        YKGTVSHDDK
        34
        GMAGGQHHHR
        35
        IKGGAEAASK
        36
        VHGEEDPTKK
        37
        KDSVAEAK
        38
        TAAHTHIK
        39
        KDKEACVHK
        40
        DYYLDLEKMISISSDGPAK
        41
        QQLSNPEFVFSDFAKFDR
        42
        HQQEVQAK
        43
        KYPEIY
        44
        GKTPLSMDQYERLFGSSR
        45
        MTAQQAPKWYPSEDVAAPK
        46
        EILDATAEALSK
        47
        KLSEESKR
        48
        DKSEAPKEEAGETNK
        49
        KKAPAGGAADAAAK
        50
        KKAPAGGAADAAAK
        First Page Previous PageNext Page Last PagePage/Total Pages

        Peptide-Spectrum Matches

        This plot shows the PSM informationin ProteomicsLFQ pipeline final result

        This table fully displays the peptide spectrum matching information in the mzTab file:

        • sequence: peptide sequence
        • unique
        • search_engine_score
        Showing 50/50 rows and 2/2 columns.
        PSM_IDsequenceunique
        0
        YPDIFPVMK
        1
        1
        KSNHNSHSSK
        1
        2
        KSNHNSHSSK
        1
        3
        PWNPPQK
        1
        4
        KHTQHK
        0
        5
        HHNEGTVSK
        1
        6
        HHNEGTVSK
        1
        7
        HHNEGTVSK
        1
        8
        HHNEGTVSK
        1
        9
        HHNEGTVSK
        1
        10
        HHNEGTVSK
        1
        11
        HHNEGTVSK
        1
        12
        HHNEGTVSK
        1
        13
        HHNEGTVSK
        1
        14
        HHNEGTVSK
        1
        15
        HHNEGTVSK
        1
        16
        HHNEGTVSK
        1
        17
        HHNEGTVSK
        1
        18
        HHNEGTVSK
        1
        19
        HHNEGTVSK
        1
        20
        HHNEGTVSK
        1
        21
        HHNEGTVSK
        1
        22
        HEDVHR
        1
        23
        HEDVHR
        1
        24
        HEDVHR
        1
        25
        HEDVHR
        1
        26
        HEDVHR
        1
        27
        HEDVHR
        1
        28
        HEDVHR
        1
        29
        HEDVHR
        1
        30
        HEDVHR
        1
        31
        HEDVHR
        1
        32
        HEDVHR
        1
        33
        HEDVHR
        1
        34
        HEDVHR
        1
        35
        HEDVHR
        1
        36
        HEDVHR
        1
        37
        HEDVHR
        1
        38
        KAEKPETK
        1
        39
        QAQEILTK
        1
        40
        IKHNKPK
        1
        41
        YDSTHGR
        0
        42
        YDSTHGR
        0
        43
        YDSTHGR
        0
        44
        YDSTHGR
        0
        45
        YDSTHGR
        0
        46
        YDSTHGR
        0
        47
        YDSTHGR
        0
        48
        YDSTHGR
        0
        49
        YDSTHGR
        0
        First Page Previous PageNext Page Last PagePage/Total Pages

        Spectra Tracking

        This plot shows the ProteomicsLFQ pipeline mzML tracking

        This table shows the changes in the number of spectra corresponding to each input file during the pipeline operation. And the number of peptides finally identified is obtained from the PSM table in the mzTab file. You can also remove the decoy with the remove_decoy parameter.:

        • MS1_Num: The number of MS1 spectra extracted from mzMLs
        • MS2_Num: The number of MS2 spectra extracted from mzMLs
        • MSGF: The Number of spectra identified by MSGF search engine
        • Comet: The Number of spectra identified by Comet search engine
        • Final result of spectra: extracted from PSM table in mzTab file
        • Final result of Peptides: extracted from PSM table in mzTab file
        Showing 27/27 rows and 3/3 columns.
        Spectra FileMS1_NumMS2_NumFinal result of spectra
        UPS1_500amol_R2.mzML
        7254
        37492
        14256
        UPS1_50000amol_R3.mzML
        6815
        41665
        14777
        UPS1_250amol_R1.mzML
        7291
        36884
        14558
        UPS1_125amol_R2.mzML
        7302
        36813
        13894
        UPS1_5000amol_R3.mzML
        7200
        38052
        14427
        UPS1_50000amol_R2.mzML
        6805
        41653
        14471
        UPS1_12500amol_R3.mzML
        6962
        39782
        14389
        UPS1_5000amol_R2.mzML
        7195
        38046
        14424
        UPS1_25000amol_R3.mzML
        6973
        40439
        15183
        UPS1_50000amol_R1.mzML
        6786
        41833
        15287
        UPS1_125amol_R1.mzML
        7277
        36802
        14368
        UPS1_500amol_R1.mzML
        7314
        37009
        14362
        UPS1_2500amol_R3.mzML
        7211
        37739
        13322
        UPS1_250amol_R2.mzML
        7275
        36887
        13605
        UPS1_2500amol_R1.mzML
        7269
        37482
        13896
        UPS1_12500amol_R2.mzML
        6976
        39682
        14531
        UPS1_125amol_R3.mzML
        7306
        36871
        13511
        UPS1_25000amol_R1.mzML
        6836
        40856
        15101
        UPS1_500amol_R3.mzML
        7288
        37342
        14090
        UPS1_250amol_R3.mzML
        7259
        37111
        14647
        UPS1_50amol_R3.mzML
        7351
        36345
        13461
        UPS1_5000amol_R1.mzML
        7213
        37918
        14033
        UPS1_25000amol_R2.mzML
        7018
        40512
        14681
        UPS1_50amol_R2.mzML
        7336
        36416
        12846
        UPS1_50amol_R1.mzML
        7302
        36443
        13051
        UPS1_12500amol_R1.mzML
        7012
        39718
        14421
        UPS1_2500amol_R2.mzML
        7247
        37556
        13990

        Distribution of precursor charges

        This is a bar chart representing the distribution of the precursor ion charges for a given whole experiment.

        This information can be used to identify potential ionization problems including many 1+ charges from an ESI ionization source or an unexpected distribution of charges. MALDI experiments are expected to contain almost exclusively 1+ charged ions. An unexpected charge distribution may furthermore be caused by specific search engine parameter settings such as limiting the search to specific ion charges.

        loading..

        Number of Peaks per MS/MS spectrum

        This chart represents a histogram containing the number of peaks per MS/MS spectrum in a given experiment. This chart assumes centroid data. Too few peaks can identify poor fragmentation or a detector fault, as opposed to a large number of peaks representing very noisy spectra. This chart is extensively dependent on the pre-processing steps performed to the spectra (centroiding, deconvolution, peak picking approach, etc).

        loading..

        Peak Intensity Distribution

        This is a histogram representing the ion intensity vs. the frequency for all MS2 spectra in a whole given experiment. It is possible to filter the information for all, identified and unidentified spectra. This plot can give a general estimation of the noise level of the spectra.

        Generally, one should expect to have a high number of low intensity noise peaks with a low number of high intensity signal peaks. A disproportionate number of high signal peaks may indicate heavy spectrum pre-filtering or potential experimental problems. In the case of data reuse this plot can be useful in identifying the requirement for pre-processing of the spectra prior to any downstream analysis. The quality of the identifications is not linked to this data as most search engines perform internal spectrum pre-processing before matching the spectra. Thus, the spectra reported are not necessarily pre-processed since the search engine may have applied the pre-processing step internally. This pre-processing is not necessarily reported in the experimental metadata.

        loading..

        Delta Mass

        This chart represents the distribution of the relative frequency of experimental precursor ion mass (m/z) - theoretical precursor ion mass (m/z).

        Mass deltas close to zero reflect more accurate identifications and also that the reporting of the amino acid modifications and charges have been done accurately. This plot can highlight systematic bias if not centered on zero. Other distributions can reflect modifications not being reported properly. Also it is easy to see the different between the target and the decoys identifications.

        loading..